The GAIA pilot at the GGS almond plantation shows how farm sensors, weather data, Earth Observation, AI recommendations and spatial context can support better-informed irrigation decisions.
GAIA has completed a dedicated agriculture case study focused on irrigation decision support in almond farming. The case study is based on the work carried out at the GGS almond plantation in Salamanca, Spain, where Xilbi Sistemas de Informacion SL and almond producer Gregorio García Sánchez have tested GAIA as a practical Agricultural Digital Solution for field monitoring and decision support.
Irrigation is one of the most relevant controllable factors in almond production. It affects water consumption, energy use, crop condition, operational cost and the environmental performance of the farm. At the same time, irrigation decisions are often based on fragmented information from soil probes, weather services, satellite indicators, field observations and the farmer’s practical experience.
GAIA addresses this challenge by bringing these sources into one operational workflow. The system combines on-farm telemetry, weather information, Earth Observation indicators, AI-based recommendations and geospatial visualisation to help the farmer review field conditions and make better-informed decisions.
The case study shows how GAIA supports a simple decision flow: the farmer reviews the dashboard, checks the field-monitoring view, interprets the relevant environmental and satellite-derived information, reviews the AI recommendation and then decides whether to follow, adjust or override the suggested action.
A central lesson from the pilot is that digital farming tools must be practical and explainable. GAIA is not designed to replace farmer judgement. It is designed to support it. Recommendations are presented as decision-support guidance, with the farmer remaining in control of the final decision.
Farmer feedback confirmed the value of reducing information fragmentation and presenting field conditions in a clearer, more actionable format. The dashboard, field view and digital twin help connect measurements and recommendations with the real layout of the plantation, while the recommendation workflow supports more structured irrigation-related decisions.
The strongest results at this stage are operational: improved data organisation, better situational awareness and a clearer basis for farmer-reviewed decision-making. Final quantified agronomic and economic results, including water-use reduction, operational-cost effects and yield-related impacts, will be consolidated using the final project evidence and available farm records.
The irrigation case study also identifies replication potential for comparable farms. The approach is especially relevant for almond and other permanent crops where irrigation, water stress, fragmented data sources and time-sensitive field decisions are important operational issues.
The next step is to use the lessons from the GGS pilot to support replication in comparable farms and regions, while keeping the solution practical, modular and farmer-centred.
Download the full case study – Supporting irrigation decisions in almond farming through GAIA
This project has received funding from the European Union’s Horizon Europe research and innovation programme under project Farmtopia (grant agreement No 101083541).
Views and opinions expressed are those of the author(s) only and do not necessarily reflect those of the European Union or the Farmtopia consortium.